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1

Shear Wave Splitting Analysis to Estimate Fracture Orientation and Frequency Dependent Anisotropy

Gholami R., Moradzadeh A., Rasouli V., Hanachi J.

Acta Geophysica

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2016

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Vol. 64, no. 1

76--100

EN

Shear wave splitting is a well-known method for indication of orientation, radius, and length of fractures in subsurface layers. In this paper, a three component near offset VSP data acquired from a fractured sandstone reservoir in southern part of Iran was used to analyse shear wave splitting and frequency-dependent anisotropy assessment. Polarization angle obtained by performing rotation on radial and transverse components of VSP data was used to determine the direction of polarization of fast shear wave which corresponds to direction of fractures. It was shown that correct implementation of shear wave splitting analysis can be used for determination of fracture direction. During frequencydependent anisotropy analysis, it was found that the time delays in shearwaves decrease as the frequency increases. It was clearly demonstrated throughout this study that anisotropy may have an inverse relationship with frequency. The analysis presented in this paper complements the studied conducted by other researchers in this field of research.

2

Shear wave velocity prediction using seismic attributes and well log data

Gholami R., Moradzadeh A., Rasouli V., Hanachi J.

Acta Geophysica

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2014

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Vol. 62, no. 4

818--848

EN

Formation’s properties can be estimated indirectly using joint analysis of compressional and shear wave velocities. Shear wave data is not usually acquired during well logging, which is most likely for cost saving purposes. Even if shear data is available, the logging programs provide only sparsely sampled one-dimensional measurements: this information is inadequate to estimate reservoir rock properties. Thus, if the shear wave data can be obtained using seismic methods, the results can be used across the field to estimate reservoir properties. The aim of this paper is to use seismic attributes for prediction of shear wave velocity in a field located in southern part of Iran. Independent component analysis (ICA) was used to select the most relevant attributes to shear velocity data. Considering the nonlinear relationship between seismic attributes and shear wave velocity, multi-layer feed forward neural network was used for prediction of shear wave velocity and promising results were presented.

3

Grade uncertainty and its impact on ore grade reconciliation between the resource model and the mine

Parhizkar A., Ataei M., Moarefvand P., Rasouli V.

Archives of Mining Sciences

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2011

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Vol. 56, no 1

119-134

EN

Major differences between estimated grade and actual grade are a usual problem in many open pit mines. The estimated grade is predicted in exploration stage from data obtained from boreholes, whereas the actual grade would be determined only after the mining operation. The poor reconciliation between the values of estimated and actual grades can cause major economic losses to the mining industry. Many different factors affect the reconciliation process in a mining operation. The nature of the orebody, the random uncertainty and the systematic errors are three main sources affecting the reconciliation process in exploration stage of the orebody. In this paper each source of uncertainty is studied and a probabilistic model is presented to determine the role of each item in total uncertainty of the grade parameter. The model ability was investigated in the study of real data taken from an iron open pit mine in Iran. The results showed the systematic uncertainty, the nature of the orebody and the random uncertainty are the main causes of poor reconciliation in the case study respectively.

PL

Poważne rozbieżności pomiędzy szacowaną a rzeczywistą jakością złóż rudy stanowią typowy problem w wielu kopalniach odkrywkowych. Szacowaną jakość określa się na etapie prac poszukiwawczych, na podstawie danych z otworów zaś rzeczywistą klasę złóż określić można jedynie w trakcie prac wydobywczych. Niewielka zgodność pomiędzy danymi szacunkowymi a rzeczywistymi powodować może znaczne straty finansowe dla sektora wydobywczego. Wiele rożnych czynników ma wpływ na poziom zgodności pomiędzy tymi danymi: charakter złoża rudy, niepewność losowa i błędy systemowe to trzy główne czynniki warunkujące poziom zgodności na etapie prac poszukiwawczych. W artykule tym zbadano te trzy główne źródła i zaproponowano model probabilistyczny dla określania roli poszczególnych czynników przyczyniających się do powstania niepewności odnośnie parametrów jakości złoża. Możliwości modelu przebadano na podstawie danych rzeczywistych uzyskanych z kopalni odkrywkowej rud żelaza w Iranie. Wyniki wskazują, że niepewność systemowa, charakter złoża i niepewność losowa w tej kolejności stanowią trzy główne czynniki warunkujące niewielki poziom zgodności pomiędzy danymi prognozowanymi a rzeczywistymi.